Darknet imaginaries in Internet memes: the discursive malleability of the cultural status of digital technologies
Bibliographic record
Abstract
Abstract Dominant discourses on the darknet present it either as a dangerous space with flourishing crime or a place for civic action and political activism. However, these depictions have been challenged in online popular culture, particularly in memes. By utilizing the concepts of double articulation of media and cultural imaginaries, this article reveals how memes shape popular definitions of darknet. Our qualitative, social semiotic content analysis of 505 memes reveals an ambiguous and complex vision of the darknet that both supports and demystifies the mainstream imagery. We introduce the concept of discursive malleability of niche technologies to describe how cultural practices reshape technologies, especially those with small userbases. Additionally, we present a “representational map of the darknet” and indicate how this contributes to social understanding of digital technologies more generally, and, not least why the analyzed memes may be read as lens exposing contradictory notions and policies regarding digital technologies nowadays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".